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FEGC
2008
104views Biometrics» more  FEGC 2008»
15 years 5 months ago
Mining Implications from Lattices of Closed Trees
We propose a way of extracting high-confidence association rules from datasets consisting of unlabeled trees. The antecedents are obtained through a computation akin to a hypergrap...
José L. Balcázar, Albert Bifet, Anto...
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
15 years 11 months ago
Scalable Algorithms for Distribution Search
Distribution data naturally arise in countless domains, such as meteorology, biology, geology, industry and economics. However, relatively little attention has been paid to data m...
Yasuko Matsubara, Yasushi Sakurai, Masatoshi Yoshi...
ICDM
2008
IEEE
97views Data Mining» more  ICDM 2008»
15 years 11 months ago
OntoDM: An Ontology of Data Mining
Motivated by the need for unification of the field of data mining and the growing demand for formalized representation of outcomes of research, we address the task of constructi...
Pance Panov, Saso Dzeroski, Larisa N. Soldatova
DMIN
2006
132views Data Mining» more  DMIN 2006»
15 years 5 months ago
Discovering Accurate and Interesting Classification Rules Using Genetic Algorithm
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exis...
Janaki Gopalan, Reda Alhajj, Ken Barker
PKDD
2000
Springer
159views Data Mining» more  PKDD 2000»
15 years 8 months ago
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...
Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda